TY - GEN AB - Literacy is one of the most fundamental skills for people to access and navigate today’s digital environment. This work systematically studies the language literacy skills of online populations for more than 160 countries and regions across the world, including many low-resourced countries where official literacy data are particularly sparse. Leveraging public data on Facebook, we develop a population-level literacy estimate for the online population that is based on aggregated and de-identified public posts written by adult Facebook users globally, significantly improving both the coverage and resolution of existing literacy tracking data. We found that, on Facebook, women collectively show higher language literacy than men in many countries, but substantial gaps remain in Africa and Asia. Further, our analysis reveals a considerable regional gap within a country that is associated with multiple socio-technical inequalities, suggesting an “inequality paradox” – where the online language skill disparity interacts with offline socioeconomic inequalities in complex ways. These findings have implications for global women’s empowerment and socioeconomic inequalities. This data is replication data for the following paper: Lin, Yu-Ru, Wu, Shaomei, and Mason, Winter (in press). Mapping Language Literacy At Scale: A Case Study on Facebook. EPJ: Data Science. DA - 2023-04-07 ED - Lin, Yu-Ru ED - Wu, Shaomei ED - Mason, Winter ED - Data Collector ED - Data Collector ED - Data Collector ID - 17 KW - literacy KW - internet use KW - inequality L1 - https://socialmediaarchive.org/record/17/files/all_country_measures.csv L1 - https://socialmediaarchive.org/record/17/files/Data%20Summary.docx L1 - https://socialmediaarchive.org/record/17/files/olle_gender_covariates.csv L1 - https://socialmediaarchive.org/record/17/files/olle_subregional_covariates.csv L1 - https://socialmediaarchive.org/record/17/files/summary_7region_OLLE.csv L1 - https://socialmediaarchive.org/record/17/files/mapping-language-literacy-data.zip L2 - https://socialmediaarchive.org/record/17/files/all_country_measures.csv L2 - https://socialmediaarchive.org/record/17/files/Data%20Summary.docx L2 - https://socialmediaarchive.org/record/17/files/olle_gender_covariates.csv L2 - https://socialmediaarchive.org/record/17/files/olle_subregional_covariates.csv L2 - https://socialmediaarchive.org/record/17/files/summary_7region_OLLE.csv L2 - https://socialmediaarchive.org/record/17/files/mapping-language-literacy-data.zip L4 - https://socialmediaarchive.org/record/17/files/all_country_measures.csv L4 - https://socialmediaarchive.org/record/17/files/Data%20Summary.docx L4 - https://socialmediaarchive.org/record/17/files/olle_gender_covariates.csv L4 - https://socialmediaarchive.org/record/17/files/olle_subregional_covariates.csv L4 - https://socialmediaarchive.org/record/17/files/summary_7region_OLLE.csv L4 - https://socialmediaarchive.org/record/17/files/mapping-language-literacy-data.zip LK - https://socialmediaarchive.org/record/17/files/all_country_measures.csv LK - https://socialmediaarchive.org/record/17/files/Data%20Summary.docx LK - https://socialmediaarchive.org/record/17/files/olle_gender_covariates.csv LK - https://socialmediaarchive.org/record/17/files/olle_subregional_covariates.csv LK - https://socialmediaarchive.org/record/17/files/summary_7region_OLLE.csv LK - https://socialmediaarchive.org/record/17/files/mapping-language-literacy-data.zip N1 - Literacy estimates are calculated for each geographically bounded community (e.g. a county or a region) with at least 1000 active users observed in the study period. The gender- or region-disaggregate population-level estimates also require a minimum of 1000 active users observed in the study period in any of the disaggregate groups. N2 - Literacy is one of the most fundamental skills for people to access and navigate today’s digital environment. This work systematically studies the language literacy skills of online populations for more than 160 countries and regions across the world, including many low-resourced countries where official literacy data are particularly sparse. Leveraging public data on Facebook, we develop a population-level literacy estimate for the online population that is based on aggregated and de-identified public posts written by adult Facebook users globally, significantly improving both the coverage and resolution of existing literacy tracking data. We found that, on Facebook, women collectively show higher language literacy than men in many countries, but substantial gaps remain in Africa and Asia. Further, our analysis reveals a considerable regional gap within a country that is associated with multiple socio-technical inequalities, suggesting an “inequality paradox” – where the online language skill disparity interacts with offline socioeconomic inequalities in complex ways. These findings have implications for global women’s empowerment and socioeconomic inequalities. This data is replication data for the following paper: Lin, Yu-Ru, Wu, Shaomei, and Mason, Winter (in press). Mapping Language Literacy At Scale: A Case Study on Facebook. EPJ: Data Science. PY - 2023-04-07 T1 - Mapping Language Literacy At Scale: A Case Study on Facebook TI - Mapping Language Literacy At Scale: A Case Study on Facebook UR - https://socialmediaarchive.org/record/17/files/all_country_measures.csv UR - https://socialmediaarchive.org/record/17/files/Data%20Summary.docx UR - https://socialmediaarchive.org/record/17/files/olle_gender_covariates.csv UR - https://socialmediaarchive.org/record/17/files/olle_subregional_covariates.csv UR - https://socialmediaarchive.org/record/17/files/summary_7region_OLLE.csv UR - https://socialmediaarchive.org/record/17/files/mapping-language-literacy-data.zip Y1 - 2023-04-07 ER -